Data, Analytics, and Insight: What's the Difference?

The world of data can be complex and tricky to navigate.  

What makes things more confusing is when the words ‘data’, ‘analytics’ and ‘insights’ are used interchangeably.  

Although it’s understandable that people often get these terms confused, each of them has an individual meaning and function.  

So what exactly is data? How is data different from analytics? And how do you get valuable insights from all that information?   

The answer can be found in three simple steps: First, you collect your data. Then you use analytics to organise and interpret that data. Finally, your insights are the knowledge and valuable actions you take away.  

Let’s explore each step in more detail:  

So how do organisations go about collecting such vast amounts of data? Data collection happens on multiple levels.  

Companies use IT systems to collect data on their customers, employees, sales, transactions and other aspects of their operation. They may also conduct marketing activities such as surveys, advertising and social media marketing, all of which will generate useful data.  

Big data refers to more complex data sets like customer databases, records, clickstreams, apps, videos and social networks. Big data is so large or complex that it’s difficult to process and analyse. Specialised data software tools are required to handle and analyse this kind of complex data.  

In order for data to be valuable, it’s important for companies to determine the type of data that needs to be collected and how the data is grouped. For example, it may be separated into clusters (or segments) such as age and income, or divided by numerical categories.  

Data must then be stored in a safe location such as a data centre or using cloud technology. Data warehousing is an important factor in data collection that can influence the scalability, consistency and performance of your data.